pydantic-yaml-parser 0.0.1

parse yaml files with pydantic

pydantic-yaml-parser

Install

pip install pydantic_yaml_parser

Background & Usage

To load YAML into a Pydantic model, you have to first convert the YAML to a dict. For example, given the below yaml file:

yaml_string="""
setting_1: Hello
setting_2:
    - kind: name
      sublist:
          - first
          - second
"""

You might define a Pydantic model to represent it like this:

from pydantic import BaseModel
from typing import List

class Setting2(BaseModel):
    kind: str
    sublist: List

class Test(BaseModel):
    setting_1: str
    setting_2: List[Setting2]

You can load the yaml file into a dict, and into the Pydantic model like so:

import yaml
yml_dict = yaml.safe_load(yaml_string)
yml_dict

{'setting_1': 'Hello',
 'setting_2': [{'kind': 'name', 'sublist': ['first', 'second']}]}

To load this dict into the pydantic model Test, you can use parse_obj:

Test.parse_obj(yml_dict)

Test(setting_1='Hello', setting_2=[Setting2(kind='name', sublist=['first', 'second'])])

However, let’s say there is an error in your yaml file such that you accidentally set sublist to false, instead of setting sublist to list type, you will get an error message that looks like this:

yaml_string="""
setting_1: ok
setting_2:
    - kind: name
      sublist: false
"""
yaml_dict_error = yaml.safe_load(yaml_string)

Test.parse_obj(yaml_dict_error)

ValidationError: 1 validation error for Test
setting_2 -> 0 -> sublist
  value is not a valid list (type=type_error.list)

This error message is a bit confusing, especially for those with no prior experience with pydantic! However when you use pydantic_yaml_parser you get something a bit clearer:

from pydantic_yaml_parser.yaml import YamlModel

class Test(YamlModel):
    setting_1: str
    setting_2: List[Setting2]

Test.from_dict(yaml_dict_error)

ValueError: Configuration error(s) for YAML:
 - value is not a valid list: `sublist` for element 0 in the list for `setting_2`